July 19, 2019  |  

Short tandem repeats, segmental duplications, gene deletion, and genomic instability in a rapidly diversified immune gene family.

Genomic regions with repetitive sequences are considered unstable and prone to swift DNA diversification processes. A highly diverse immune gene family of the sea urchin (Strongylocentrotus purpuratus), called Sp185/333, is composed of clustered genes with similar sequence as well as several types of repeats ranging in size from short tandem repeats (STRs) to large segmental duplications. This repetitive structure may have been the basis for the incorrect assembly of this gene family in the sea urchin genome sequence. Consequently, we have resolved the structure of the family and profiled the members by sequencing selected BAC clones using Illumina and PacBio approaches.BAC insert assemblies identified 15 predicted genes that are organized into three clusters. Two of the gene clusters have almost identical flanking regions, suggesting that they may be non-matching allelic clusters residing at the same genomic locus. GA STRs surround all genes and appear in large stretches at locations of putatively deleted genes. GAT STRs are positioned at the edges of segmental duplications that include a subset of the genes. The unique locations of the STRs suggest their involvement in gene deletions and segmental duplications. Genomic profiling of the Sp185/333 gene diversity in 10 sea urchins shows that no gene repertoires are shared among individuals indicating a very high gene diversification rate for this family.The repetitive genomic structure of the Sp185/333 family that includes STRs in strategic locations may serve as platform for a controlled mechanism which regulates the processes of gene recombination, gene conversion, duplication and deletion. The outcome is genomic instability and allelic mismatches, which may further drive the swift diversification of the Sp185/333 gene family that may improve the immune fitness of the species.

July 7, 2019  |  

A genomic view of short tandem repeats.

Short tandem repeats (STRs) are some of the fastest mutating loci in the genome. Tools for accurately profiling STRs from high-throughput sequencing data have enabled genome-wide interrogation of more than a million STRs across hundreds of individuals. These catalogs have revealed that STRs are highly multiallelic and may contribute more de novo mutations than any other variant class. Recent studies have leveraged these catalogs to show that STRs play a widespread role in regulating gene expression and other molecular phenotypes. These analyses suggest that STRs are an underappreciated but rich reservoir of variation that likely make significant contributions to Mendelian diseases, complex traits, and cancer. Copyright © 2017 Elsevier Ltd. All rights reserved.

July 7, 2019  |  

STR-realigner: a realignment method for short tandem repeat regions.

In the estimation of repeat numbers in a short tandem repeat (STR) region from high-throughput sequencing data, two types of strategies are mainly taken: a strategy based on counting repeat patterns included in sequence reads spanning the region and a strategy based on estimating the difference between the actual insert size and the insert size inferred from paired-end reads. The quality of sequence alignment is crucial, especially in the former approaches although usual alignment methods have difficulty in STR regions due to insertions and deletions caused by the variations of repeat numbers.We proposed a new dynamic programming based realignment method named STR-realigner that considers repeat patterns in STR regions as prior knowledge. By allowing the size change of repeat patterns with low penalty in STR regions, accurate realignment is expected. For the performance evaluation, publicly available STR variant calling tools were applied to three types of aligned reads: synthetically generated sequencing reads aligned with BWA-MEM, those realigned with STR-realigner, those realigned with ReviSTER, and those realigned with GATK IndelRealigner. From the comparison of root mean squared errors between estimated and true STR region size, the results for the dataset realigned with STR-realigner are better than those for other cases. For real data analysis, we used a real sequencing dataset from Illumina HiSeq 2000 for a parent-offspring trio. RepeatSeq and lobSTR were applied to the sequence reads for these individuals aligned with BWA-MEM, those realigned with STR-realigner, ReviSTER, and GATK IndelRealigner. STR-realigner shows the best performance in terms of consistency of the size of estimated STR regions in Mendelian inheritance. Root mean squared error values were also calculated from the comparison of these estimated results with STR region sizes obtained from high coverage PacBio sequencing data, and the results from the realigned sequencing data with STR-realigner showed the least (the best) root mean squared error value.The effectiveness of the proposed realignment method for STR regions was verified from the comparison with an existing method on both simulation datasets and real whole genome sequencing dataset.

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